• The Transactions of the Korea Information Processing Society
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• v.6 no.12
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• pp.3469-3476
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• 1999

In spatial database based on spatial data structures, instead of one-dimensional indexing structure, new indexing structure which corresponds to multi-dimensional features of spatial objects is required. In order to meet those requirements, in this paper we proposed new indexing structure for efficient retrieval of spatial database by carrying through the feature analysis of conventional multi-dimensional indexing structures. To improve the sequential search method of supernodes in the conventional X-tree and to reduce the retrieval time in case of generating the huge supernode, we proposed a indexing structure integrating the kd-tree based on point index structure into the X-tree. We implemented the proposed indexing structure and analyzed its retrieval time according to the dimension and distribution of experimental data.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.451-463
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• 2003

Recently, there have been various research efforts to develop strategies for accelerating OLAP operations on huge amounts of spatio-temporal data. Most of the work is based on multi-tree structures which consist of a single R-tree variant for spatial dimension and numerous B-trees for temporal dimension. The multi~tree based frameworks, however, are hardly applicable to spatio-temporal OLAP in practice, due mainly to high management cost and low query efficiency. To overcome the limitations of such multi-tree based frameworks, we propose a new approach called Hilbert Cube(H-Cube), which employs fractals in order to impose a total-order on cells. In addition, the H-Cube takes advantage of the traditional Prefix-sum approach to improve Query efficiency significantly. The H-Cube partitions an embedding space into a set of cells which are clustered on disk by Hilbert ordering, and then composes a cube by arranging the grid cells in a chronological order. The H-Cube refines cells adaptively to handle regional data skew, which may change its locations over time. The H-Cube is an adaptive, total-ordered and prefix-summed cube for spatio-temporal data warehouses. Our approach focuses on indexing dynamic point objects in static spatial dimensions. Through the extensive performance studies, we observed that The H-Cube consumed at most 20% of the space required by multi-tree based frameworks, and achieved higher query performance compared with multi-tree structures.

• Journal of Korea Multimedia Society
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• v.12 no.10
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• pp.1386-1396
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• 2009

Most decision support functions of spatial data warehouse rely on the OLAP operations upon a spatial cube. Meanwhile, higher performance is always guaranteed by indexing the cube, which stores huge amount of pre-aggregated information. Hierarchical Dwarf was proposed as a solution, which can be taken as an extension of the Dwarf, a compressed index for cube structures. However, it does not consider the spatial dimension and even aggregates incorrectly if there are redundant values at the lower levels. OLAP-favored Searching was proposed as a spatial hierarchy based OLAP operation, which employs the advantages of R-tree. Although it supports aggregating functions well against specified areas, it ignores the operations on the spatial dimensions. In this paper, an indexing approach, which aims at utilizing the concept hierarchy of the spatial cube for decision support, is proposed. The index consists of concept hierarchy trees of all dimensions, which are linked according to the tuples stored in the fact table. It saves storage cost by preventing identical trees from being created redundantly. Also, it reduces the OLAP operation cost by integrating the spatial and aspatial dimensions in the virtual concept hierarchy.

• KIISE Transactions on Computing Practices
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• v.20 no.11
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• pp.610-614
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• 2014

Like many types of scientific data, results from simulations of volcanic ash diffusion are of a clustered sparse matrix in the netCDF format. Since these data sets are large in size, they generate high storage and transmission costs. In this paper, we suggest a new method that reduces the size of the data of volcanic ash diffusion simulations by converting the multi-dimensional index to a single dimension and keeping only the starting point and length of the consecutive zeros. This method presents performance that is almost as good as that of ZIP format compression, but does not destroy the netCDF structure. The suggested method is expected to allow for storage space to be efficiently used by reducing both the data size and the network transmission time.

• KIEAE Journal
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• v.10 no.6
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• pp.115-121
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• 2010

This paper is an outgrowth of many years of practicing real interior work projects and one of my responses to the question not only about the actual dimension of interior work surface but also about the classification of contemporary finishing materials in basic interior project of high-rise apartment houses. For this purpose, 8 conventional apartment units which are already-built or designed have been surveyed and the results are interpreted in the form of proportion of space and finishes. The data can be applied to make up a schematic design in the selection of environment-friendly interior works and assessment of the degree of sustainability. For further study, the basic data provided here can be used as an index to differentiate the occupants' desire toward green interior design for their own apartment spaces, comparing to the conventional interior work in the Korean market. Not surprisingly, wall paper is dominated to make the interior surface in apartment houses. In the percentile of the utilization of finishing materials, wood-flooring and coating materials like wet paint also ranked at the upper position.

• Korean Journal of Remote Sensing
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• v.32 no.1
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• pp.1-11
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• 2016

Since forest is an important part of ecological system, the deforestation is one of global substantive issues. It is generally accepted that the climate change is related to the deforestation. The issue is worse in developing countries because the forest is one of important natural resources. In the case of North Korea, the deforestation is on the rise from forest reclamation for firewood collection and food production. Moreover, a secondary effect from flood intensifies the damage. Also, the political situation in North Korea presents difficulty to have in-situ measurements. It means that the accurate information of North Korea is nearly impossible to obtain. Thus, assessing the current situation of the forest in North Korea by indirect method is required. The objective of this study is to monitor the forest status of North Korea using multitemporal Landsat images, from 1980s to 2010s. Since the deforestation in North Korea is caused by local residents, we selected two study areas of high population density: Pyeongyang and Hyesan. In North Korea, most of clean Landsat images are acquired in fall season. The fall images have an advantage that we can easily distinguish agriculture areas from forest areas, also have an disadvantage that the forests cannot be easily identified because some of trees have turned red. To identify the forests exactly, we proposed a modified Normalized Difference Vegetation Index (mNDVI) value. The deforestation in Pyeongyang and Hyesan was analyzed by using mNDVI. The dimension of forest has decreased approximately 36% in Pyeongyang for 27 years and approximately 25% in Hyesan for 16 years. The results show that the forest areas in Pyeongyang and Hyesan have been steadily reduced.

• The KIPS Transactions:PartD
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• v.9D no.5
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• pp.779-788
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• 2002

There are many technically difficult issues in searching multimedia data such as image, video and audio because they are massive and more complex than simple text-based data. As a method of searching multimedia data, a similarity retrieval has been studied to retrieve automatically basic features of multimedia data and to make a search among data with retrieved features because exact match is not adaptable to a matrix of features of multimedia. In this paper, data clustering and its indexing are proposed as a speedy similarity-retrieval method of multimedia data. This approach clusters similar images on adjacent disk cylinders and then builds Indexes to access the clusters. To minimize the search cost, the hashing is adapted to index cluster. In addition, to reduce I/O time, the proposed searching takes just one I/O to look up the location of the cluster containing similar object and one sequential file I/O to read in this cluster. The proposed schema solves the problem of multi-dimension by using clustering and its indexing and has higher search efficiency than the content-based image retrieval that uses only clustering or indexing structure.

• The Journal of Korean Physical Therapy
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• v.26 no.5
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• pp.351-357
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• 2014

Purpose: The purpose of this study was to investigate level of functioning in patients with stroke using Modified Bathel Index (MBI), World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0), and ICF core-set for stroke. Methods: Sixty-four patients with stroke were recruited for this study from nine medical institutes. The ICF core-set for stroke, WHODAS 2.0, and MBI were used to collect subjects' functional levels. ICF core-set was employed here as a standard frame to observe multi-dimension of functioning, that is physiological bodily function, activity and participation (AP) in daily life, and current environmental factors (EF) in patients with stroke. WHODAS 2.0 and MBI were also used in order to have a specific functioning level for subjects. The linkage of each item in WHODAS 2.0 and MBI into the ICF core-set for stroke was examined. Pearson correlation coefficient was used for analysis of their relationships. Results: Functioning level of participants showed moderate resulting from MBI and WHODAS 2.0 ($73.48{\pm}22.27$ and $35.55{\pm}12.53$, respectively). Strong relationship was observed between ICF core-set and WHODAS 2.0, and with MBI. Each item of disability scales was obtained its linkage into ICF in the domain of AP. However, lack of correlation between MBI and ICF in the domain of EF was found due to absence of related factors. Conclusion: MBI was found to be linked mainly into ICF in the domain of AP and to have limited linkage into EF. Therefore, it should be suggested that the ICF concept frame should be used as a multi-dimensional approach to patients with stroke.

• The Journal of the Acoustical Society of Korea
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• v.34 no.4
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• pp.264-273
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• 2015

Improvement of the radiation beam profile of a medical ultrasonic transducer has been researched in this paper. In order to improve the beam profile, a new transducer structure has been devised that includes both a shaded electrode and a multi-focus lens. For a linear sound source, the beam profile was investigated through finite element analysis, and then the optimal design of the devised structure was carried out by considering such performances as sidelobe level, focal range and beamwidth simultaneously. In the process, the optimal dimension of the devised structure was derived by using the ratio of the focal range to the minimum beamwidth as a performance index. As a result, the beam profile has been improved to have a lower sidelobe level at -20.2 dB and a consistent narrow beamwidth from 30 mm to 160 mm depth with the minimum beamwidth at 2.04 mm. Further, a prototype transducer was fabricated to have the devised structure, and its performance was measured and compared with the analysis results to confirm the validity of the devised transducer structure.

• Journal of KIISE:Databases
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• v.31 no.5
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• pp.468-478
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• 2004

It is essential in various application areas of data mining and bioinformatics to effectively retrieve the occurrences of interesting patterns from sequence databases. For example, let's consider a network event management system that records the types and timestamp values of events occurred in a specific network component(ex. router). The typical query to find out the temporal casual relationships among the network events is as fellows: 'Find all occurrences of CiscoDCDLinkUp that are fellowed by MLMStatusUP that are subsequently followed by TCPConnectionClose, under the constraint that the interval between the first two events is not larger than 20 seconds, and the interval between the first and third events is not larger than 40 secondsTCPConnectionClose. This paper proposes an indexing method that enables to efficiently answer such a query. Unlike the previous methods that rely on inefficient sequential scan methods or data structures not easily supported by DBMSs, the proposed method uses a multi-dimensional spatial index, which is proven to be efficient both in storage and search, to find the answers quickly without false dismissals. Given a sliding window W, the input to a multi-dimensional spatial index is a n-dimensional vector whose i-th element is the interval between the first event of W and the first occurrence of the event type Ei in W. Here, n is the number of event types that can be occurred in the system of interest. The problem of‘dimensionality curse’may happen when n is large. Therefore, we use the dimension selection or event type grouping to avoid this problem. The experimental results reveal that our proposed technique can be a few orders of magnitude faster than the sequential scan and ISO-Depth index methods.hods.